Since 2006, 23andMe’s mission has been to help people access, understand, and benefit from the human genome. We are a group of passionate individuals pushing the boundaries of what’s possible to help turn genetic insight into better health and personal understanding.
Our Therapeutics team, which was established more than five years ago, has been actively identifying novel drug targets using 23andMe’s unparalleled database and developing a portfolio across several therapeutic areas, including oncology and cardiovascular and metabolic disease. More information about our Therapeutics team is available at https://therapeutics.23andme.com/.
We are looking for a quantitative scientist with extensive experience in computational biology. Ideal candidates will have demonstrated experience conducting creative and independent research analyzing a broad range of public or internally generated genomic datasets, with an emphasis on understanding the underlying biology.
Join our collaborative, cross-functional research team focused on discovery of novel therapeutic targets and their development in our laboratories!
What you’ll do
Biological interpretation of genetic signals available to 23andMe, which requires computational methods to analyze high-throughput functional data
Development of tools and reports that integrate genetics and functional genomics to drive target discovery and summarizing the results in ways that enable efficient decision making
Extend existing target discovery efforts to incorporate additional data types and novel analysis methods; work toward identifying clinically relevant disease subtypes and associated therapeutic targets; and contribute to on-going therapeutic development programs
Communicate ideas and results to other scientists
What you’ll bring
Ph.D. in Computational Biology, Bioinformatics, Biostatistics, Genetics or a related field
Knowledge of biology in at least one disease-relevant area (e.g., cardiovascular diseases, oncology, immunology, etc.)
Hands-on experience in analysis of RNA-seq or microarrays, and other large scale omics datasets
Fluency with tools and methods for processing functional sequencing data (RNA-seq, ATAC-seq, ChIP-seq or similar)
Strong quantitative skills and a background in statistical data analysis or machine learning
Experience in writing robust code in R or python
Exceptional communication skills, with an ability to convey complex computational results to colleagues from a wide range of life sciences backgrounds
Ability to work in a dynamic team-oriented environment
Industry experience in pharmaceuticals or biotechnology
Expertise in genetics and/or fine mapping of genetic association signals
Extensive experience in writing robust code in a shared development environment
Note: Job title will be commensurate with experience and academic credentials